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Viaccieľový simulovaný žíhanie (MOSA)×Multi-Objective Genetic Algorithm (MOGA)×
OdborSimuláciaSimulácia
RodinaProcess / pipelineProcess / pipeline
Rok vzniku1992–19981984
TvorcaSerafini, P.; Czyzak, P. and Jaszkiewicz, A.Schaffer, J. D. (early MOGA); Goldberg, D. E. (GA foundations)
TypMetaheuristic / Pareto-based optimizerPopulation-based evolutionary optimizer
Pôvodný zdrojCzyzak, P., Jaszkiewicz, A. (1998). Pareto simulated annealing — a metaheuristic technique for multiple-objective combinatorial optimization. Journal of Multi-Criteria Decision Analysis, 7(1), 34–47. DOI ↗Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning. Addison-Wesley. ISBN: 9780201157673
Ďalšie názvyMOSA, Multi-Criteria Simulated Annealing, Pareto Simulated Annealing, PSAMOGA, Multi-objective GA, Evolutionary multi-objective optimization, EMO
Príbuzné54
ZhrnutieMulti-Objective Simulated Annealing (MOSA) extends the classical simulated annealing metaheuristic to problems with two or more conflicting objective functions. Instead of converging to a single optimum, MOSA explores the solution space stochastically and maintains an archive of non-dominated (Pareto-optimal) solutions, offering decision-makers a diverse trade-off front rather than one prescribed answer.A Multi-Objective Genetic Algorithm (MOGA) is an evolutionary computation method that evolves a population of candidate solutions toward a Pareto-optimal front, simultaneously optimizing two or more conflicting objective functions. It avoids collapsing trade-offs into a single score, instead producing a set of non-dominated solutions for the decision-maker to choose among.
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ScholarGatePorovnať metódy: Multi-objective simulated annealing · Multi-objective genetic algorithm. Získané 2026-06-15 z https://scholargate.app/sk/compare